Irrigation scheduling for Sovereign Coronation grapevine based upon evapotranspiration calculations and crop coefficients /
Notice bibliographique
Résumé
Several irrigation treatments were evaluated on Sovereign Coronation table grapes at two \nsites over a 3-year period in the cool humid Niagara Peninsula of Ontario. Trials were conducted \nin the Hippie (Beamsville, ON) and the Lambert Vineyards (Niagara-on-the-Lake, ON) in 2003 \nto 2005 with the objective of assessing the usefulness of the modified Penman-Monteith equation \nto accurately schedule vine irrigation needs. Data (relative humidity, windspeed, solar radiation, \nand temperature) required to precisely calculate evapotranspiration (ETq) were downloaded from \nthe Ontario Weather Network. One of two ETq values (either 100 or 150%) were used in \ncombination with one of two crop coefficients (Kc; either fixed at 0.75 or 0.2 to 0.8 based upon \nincreasing canopy volume) to calculate the amount of irrigation water required. Five irrigation \ntreatments were: un irrigated control; (lOOET) X Kc =0.75; 150ET X Kc =0.75; lOOET X Kc \n=0.2-0.8; 150ET X Kc =0.2-0.8. Transpiration, water potential (v|/), and soil moisture data were \ncollected each growing seasons. Yield component data was collected and berries from each \ntreatment were analyzed for soluble solids (Brix), pH, titratable acidity (TA), anthocyanins, \nmethyl anthranilate (MA), and total volatile esters (TVE). Irrigation showed a substantial \npositive effect on transpiration rate and soil moisture; the control treatment showed consistently \nlower transpiration and soil moisture over the 3 seasons. Transpiration appeared accurately \nreflect Sovereign Coronation grapevines water status. Soil moisture also accurately reflected \nlevel of irrigation. Moreover, irrigation showed impact of leaf \\|/, which was more negative \nthroughout the 3 seasons for vines that were not irrigated. Irrigation had a substantial positive \neffect on yield (kg/vine) and its various components (clusters/vine, cluster weight, and \nberries/cluster) in 2003 and 2005. Berry weights were higher under the irrigated treatments at \nboth sites. Berry weight consistently appeared to be the main factor leading to these increased \nyields, as inconsistent responses were noted for some yield variables. Soluble solids was highest under the ET150 and ET100 treatments both with Kc at 0.75. Both pH and TA were highest \nunder control treatments in 2003 and 2004, but highest under irrigated treatments in 2005. \nAnthocyanins and phenols were highest under the control treatments in 2003 and 2004, but \nhighest under irrigated treatments in 2005. MA and TVE were highest under the ET150 \ntreatments. Vine and soil water status measurements (soil moisture, leaf \\|/, and transpiration) \nconfirmed that irrigation was required for the summers of 2003 and 2005 due to dry weather in \nthose years. They also partially supported the hypothesis that the Penman-Monteith equation is \nuseful for calculating vineyard water needs. Both ET treatments gave clear evidence that \nirrigation could be effective in reducing water stress and for improving vine performance, yield \nand fruit composition. Use of properly scheduled irrigation was beneficial for Sovereign \nCoronation table grapes in the Niagara region. Findings herein should give growers some strong \nguidehnes on when, how and how much to irrigate their vineyards.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».